用变分描述子分析哈欠检测驾驶员困倦状态

Belhassen Akrout, W. Mahdi
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引用次数: 29

摘要

随着交通事故数量的大幅增加,道路安全问题已被一些国家所关注。困倦是造成交通事故的原因之一。与瞌睡有关的事故不仅发生在高速公路上,也发生在主干道上,甚至在地方内部。如今,随着计算机视觉技术的发展,检测驾驶员的疲劳状态已经成为可能。生理学研究结果表明,第一级警觉性缺乏表现为打哈欠频率的增加。在这项工作中,我们提出了一种新的打哈欠检测方法来监测驾驶员疲劳。事实上,我们的方法依赖于对非平稳和非线性信号的时空描述符的研究。该方法由YawDD[1]和我们的MiraclHB[2]数据库进行评估。评价显示了许多有希望的结果,表明了所建议方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness
The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.
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